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Published on: November 27, 2019
A systematic review and meta-analysis of the Everyday Discrimination Scale and biomarker outcomes
Jourdyn A Lawrence1, Ichiro Kawachi2, Kellee White3
1Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Population Health Sciences, Harvard Graduate School of Arts and Sciences, Cambridge, MA, USA; François-Xavier Bagnoud (FXB) Center for Health and Human Rights, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Abstract:
Discrimination has consistently been associated with multiple adverse health outcomes. Like other psychosocial stressors, discrimination is thought to impact health through stress-related physiologic pathways including hypothalamic-pituitary-adrenal (HPA) axis activation, dysregulation of inflammation responses, and accelerated cellular aging. Given growing attention to research examining the biological pathways through which discrimination becomes embodied, this systematic review and meta-analysis synthesizes empirical evidence examining relationships between self-reported discrimination and four biomarker outcomes (i.e., cortisol, C-reactive protein (CRP), interleukin-6 (IL-6), and telomere length) among studies that have used the Everyday Discrimination Scale. We conducted a systematic review of studies discussing self-reported, everyday, or chronic discrimination in the context of health by searching Medline / PubMed (National Library of Medicine, NCBI), PsycInfo (APA, Ebsco) and Web of Science Core Collection (Clarivate). Twenty-five articles met the criteria for meta-analysis, with several reporting on multiple outcomes. Discrimination was associated with elevated CRP levels (r = 0.11; 95% CI: 0.01, 0.20, k = 10), though not cortisol (r = 0.05; 95% CI: -0.06, 0.16, k = 9), IL-6 (r = 0.05; 95% CI: -0.32, 0.42, k = 5), or telomere length (r = 0.03; 95% CI: -0.01, 0.07, k = 6). We identify several points of consideration for future research including addressing heterogeneity in assessment of biomarker outcomes and the need for longitudinal assessments of relationships between discrimination and biomarker outcomes.
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